Charbonneau, P., Gish, C., Hoy, R. & Morse, P. (2021). Data from: thermodynamic stability of hard sphere crystals in dimensions 3 through 10. Duke Research Data Repository. https://doi.org/10.7924/r4jh3mw3w
Olander, L., Shepard, C., Tallis, H., & Yoskowitz, D. (2021). Data from: Gulf of Mexico Ecosystem Service Logic Models & Socio-Economic Indicators (GEMS). Duke Research Data Repository. https://doi.org/10.7924/r4s181m3h
Hayes, M., Puckett, B., Deaton, C. & Ridge, J. (2021). Data from: estimating dredge-induced turbidity using drone imagery. Duke Research Data Repository. https://doi.org/10.7924/r49z9756z
Mooney, R., Ben-Tov, M., & Duarte, F. (2021). Data from: a neural hub that coordinates learned and innate courtship behaviors. Duke Research Data Repository. https://doi.org/10.7924/r4fq9z00b
Ciocanel, V. (2021). Data and scripts from: Actin reorganization throughout the cell cycle mediated by motor proteins. Duke Research Data Repository. https://doi.org/10.7924/r4zp43t43
Riska, K., Peskoe, S., Gordee, A., Kuchibhatla, M., & Smith, S. (2021). Data from: preliminary evidence on the impact of hearing aid use on falls risk in individuals with self-reported hearing loss. Duke Research Data Repository. https://doi.org/10.7924/r43f4tf93
Patterson, L. & Doyle, M. (2021). Data and scripts from: exploring the affordability of water services across and within utilities in the United States. Duke Research Data Repository. https://doi.org/10.7924/r4862k514
Andersen, S. H., Richmond-Rakerd, L. S., Moffitt, T. E., & Caspi, A. (2021). Scripts from: Nationwide evidence that education disrupts the intergenerational transmission of disadvantage. Duke Research Data Repository. https://doi.org/10.7924/r4vx0dx06
Walker, I., Montaño, M., Lankone, R., Fairbrother, H. & Ferguson, L. (2021). Data from: Influence of CNT loading and environmental stressors on leaching of polymer associated chemicals from epoxy and polycarbonate nanocomposites. Duke Research Data Repository. https://doi.org/10.7924/r4r49q34n
Bierlich, K. C., Schick, R. S., Hewitt, J., Dale, J., Goldbogen, J. A., Friedlaender, A. S., & Johnston, D. W. (2020). Data and scripts from: A Bayesian approach for predicting photogrammetric uncertainty in morphometric measurements derived from UAS. Duke Research Data Repository. V2 https://doi.org/10.7924/r4sj1jj6s
Charbonneau, B., Charbonneau, P., Hu, Y., & Yang, Z. (2021). Data and scripts from: High-dimensional percolation criticality and hints of mean-field-like caging of the random Lorentz gas. Duke Research Data Repository. https://doi.org/10.7924/r4s46r07b
Warnell, K., & Olander, L. (2021). Pocosin wetland status and owner type for North Carolina. Duke Research Data Repository. https://doi.org/10.7924/r4s75fc6q
Charbonneau, P. & Tarzia, M. (2021). Data from: Solution of disordered microphases in the Bethe approximation. Duke Research Data Repository. https://doi.org/10.7924/r42v2m409
Charbonneau, P., Corwin, E. I., Dennis, R. C., Díaz Hernández Rojas, R., Ikeda, H., Parisi, G., & Ricci-Tersenghi, F. (2021). Data and scripts from: Finite size effects in the microscopic critical properties of jammed configurations: a comprehensive study of the effects of different types of disorder. Duke Research Data Repository. https://doi.org/10.7924/r4833vm1m
Hale, L. (2021). Data from: Liver and biliary disease in mice with ulcerative colitis-like colon inflammation. Duke Research Data Repository. https://doi.org/10.7924/r4ws8r786
Zheng, M., & Charbonneau, P. (2021). Data and scripts from: Characterization and efficient Monte Carlo sampling of disordered microphases. Duke Research Data Repository. https://doi.org/10.7924/r4w37th8b
Fogel, A. S., McLean, E. M., Gordon, J. B., Archie, E. A., Tung, J., & Alberts, S. C. (2021). Data from: Genetic ancestry predicts male-female affiliation in a natural baboon hybrid zone. Duke Research Data Repository. https://doi.org/10.7924/r4kp82d1z
Hu, Y., & Charbonneau, P. (2021). Data and scripts from: Percolation thresholds on high-dimensional D_n and E_8-related lattices. Duke Research Data Repository. https://doi.org/10.7924/r4fx7bk95
Cassar, I. R., & Grill, W. M. (2021). Data from: Therapeutic frequency profile of subthalamic nucleus deep brain stimulation is shaped by antidromic spike failure. Duke Research Data Repository. https://doi.org/10.7924/r41n85692
Biroli, G., Charbonneau, P., Hu, Y., Ikeda, H., Szamel, G., & Zamponi, F. (2021). Data from: Mean-field caging in a random Lorentz gas. Duke Research Data Repository. https://doi.org/10.7924/r4sb44m3b
Goffinet, J., Brudner, S., Mooney, R., & Pearson, J. (2021). Data from: Low-dimensional learned feature spaces quantify individual and group differences in vocal repertoires. Duke Research Data Repository. https://doi.org/10.7924/r4gq6zn8w
Lerch, B., Abbott, K., Archie, E., & Alberts, S. (2021). Data from: Better baboon breakups: collective decision theory of complex social network fissions. Duke Research Data Repository. https://doi.org/10.7924/r4bz67v25
Cassar, I. R., & Grill, W. M. (2021). Data from: The cortical evoked potential as a biomarker for deep brain stimulation efficacy. Duke Research Data Repository. https://doi.org/10.7924/r4r78d86s
Teti, Z., & Blumsack, S. (2021). RTOGov: regional transmission organization member voting data. Duke Research Data Repository. https://doi.org/10.7924/r40k2dx36
Morse, P. K., Roy, S., Agoritsas, E., Stanifer, E., Corwin, E. I., & Manning, M. L. (2021). Data from: A direct link between active matter and sheared granular systems. Duke Research Data Repository. https://doi.org/10.7924/r4cv4kb23
Crewmembers of the Eastward. (2021). Research Vessel Eastward science logs, 1971 and 1975-1981. Duke Research Data Repository. https://doi.org/10.7924/r4dz09m64
Charbonneau, P. & Hu, Y. (2021). Data and scripts from: Resolving the two-dimensional ANNNI model using transfer matrices. Duke Research Data Repository. https://doi.org/10.7924/r4k074j0t
Nieman, C. M., Rudman, A. N., Chory, M. L., Murray, G., Fairbanks, L., & Campbell, L. M. (2021). Data from: Fishing for food: values and benefits associated with coastal infrastructure. Duke Research Data Repository. https://doi.org/10.7924/r4057m91d
Biroli, G., Charbonneau, P., Corwin, E. I., Hu, Y., Ikeda, H., Szamel, G., & Zamponi, F. (2021). Data and Scripts from: Interplay between percolation and glassiness in the random Lorentz gas. Duke Research Data Repository. https://doi.org/10.7924/r4qz29054
Jordans, M. J. D., Kohrt, B. A., Sangraula, M., Turner, E. L., Wang, X., Shrestha, P., Ghimire, R., Van‘t Hof, E., Bryant, R. A., Dawson, K., Marahatta, K., Luitel, N. P., & Van Ommeren, M. (2021). Data from: Effectiveness of Group Problem Management Plus a brief psychological intervention for adults affected by humanitarian disasters in Nepal: a cluster randomized controlled trial. Duke Research Data Repository. https://doi.org/10.7924/r4gh9jq3g.
Crewmembers of the Dan Moore. (2021). Research vessel Dan Moore station logs, 1968-1981. Duke Research Data Repository. V2 https://doi.org/10.7924/r41j9fq8z
Charbonneau, P. & Morse, P. (2021). Data From: Memory formation in jammed hard spheres. Duke Research Data Repository. https://doi.org/10.7924/r41r6vf5t
Getzinger, G. J., Higgins, C. P., & Ferguson, P. L. (2021). Data and scripts from: A structure database and in silico spectral library for comprehensive suspect screening of per- and polyfluoroalkyl substances (PFASs) in environmental media by high-resolution mass spectrometry. Duke Research Data Repository. V2 https://doi.org/10.7924/r4q23zg65
Peña, E., Pelot, N. A., & Grill, W. M. (2021). Data from: Non-monotonic kilohertz frequency neural block thresholds arise from amplitude- and frequency-dependent charge imbalance. Duke Research Data Repository. https://doi.org/10.7924/r4pn94v5h
Murphy, S., Berchuck, A., Whitaker, R., Sfakianos, G. & Huang, Z. (2021). Gene Expression using Affymetrix Human Genome U133 Plus 2 Arrays from 16 Primary and Recurrent Serous Epithelial Ovarian Cancers. Duke Research Data Repository. https://doi.org/10.7924/r43f4sx2k
Murphy, S. K., Berchuk, A., Whitaker, R., Sfakianos, G., & Huang, Z. (2021). Primary and recurrent (second-look surgery) serous epithelial ovarian cancers Illumina Infinium HumanMethylation450 BeadChip data. Duke Research Data Repository. https://doi.org/10.7924/r4765hq57
Hale, L., Cheatham, L., Macintyre, A., LaFleur, B., Sanders, B., Troy, J., Kurtzberg, J., & Sempowski, G. (2021). Data and Code from: T Cell-Depleted Cultured Pediatric Thymus Tissue as a Model for Some Aspects of Human Age-Related Thymus Involution. Duke Research Data Repository. https://doi.org/10.7924/r47d2xg50
Michael, V., Goffinet, J. Pearson, J., Wang, F., Tschida, K., & Mooney, R. (2020). Data and scripts from: Circuit and synaptic organization of forebrain-to-midbrain pathways that promote and suppress vocalization. Duke Research Data Repository. https://doi.org/10.7924/r4cz38d99.
Taylor, I., Lehner, K., McCaskey, E., Nirmal, N., Ozkan-Aydin, Y., Murray-Cooper, M., Jain, R., Hawkes, E. W., Ronald, P. C., Goldman, D. I., & Benfey, P. N. (2020). Data and scripts from: Mechanism and function of root circumnutation. Duke Research Data Repository. https://doi.org/10.7924/r4b27x11m
Warnell, K., & Olander, L. (2020). Data from: Coastal protection and blue carbon mapping for six mid-Atlantic states. Duke Research Data Repository. https://doi.org/10.7924/r4pg1qw8p
Huang, A. (2020). Data from: Lightning Initiation from Fast Negative Breakdown is Led by Positive Polarity Dominated Streamers. Duke Research Data Repository. https://doi.org/10.7924/r44m97j8v
Zhang, Y., Wang, Z., Kouznetsova, T., Sha, Y., Xu, E., Shannahan, L., Fermen-Coker, M., Lin., Y. (2020). Data from: Distal conformational locks on ferrocene mechanophores guide reaction pathways for increased mechanochemical reactivity. V3 Duke Research Data Repository. https://doi.org/10.7924/r4gq6z428
Zipple, M., Altmann, J., Campos, F., Cords, M., Lawler, R., Londsdorf, E., Perry, S., Pusey, A., Stoinski, T. Strier, K., Alberts, S. (2020). Data from: Beyond orphaned infants: novel effects of maternal death in wild primates. Duke Research Data Repository. https://doi.org/10.7924/r44f1tk8k
Clark, J.S., Andrus, R., Aubry-Kientz, M., Bergeron, Y., Bogdziewicz, M., Bragg, D.C., Brockway, D., Cleavitt, N.L., Cohen, S., Courbaud, B., Daley, R., Das, A.J., Dietze, M., Fahey, T.J., Fer, I., Franklin, J.F., Gehring, C.A., Gilbert, G.S., Greenberg, C.H., ... Zlotin, R. (2020). Data from: Continent-wide tree fecundity driven by indirect climate effects. Duke Research Data Repository. https://doi.org/10.7924/r4348ph5t
Barth, B., Grill, W., Spencer, N., & Travis, L. (2020). Data from: The control of colonic motility using electrical stimulation to modulate enteric neural circuitry. Duke Research Data Repository. https://doi.org/10.7924/r4bk1dq8n
DeLaMater, D. S., Couture, J. J., Puzey, J. R., & Dalgleish, H. J. (2020). Data from: Range-wide variations in common milkweed traits and their effect on monarch larvae. Duke Research Data Repository. https://doi.org/10.7924/r4gb24j1x
Dohlman, A., Arguijo Mendoza, D., Ding, S., Gao, M., Dressman, H., Iliev, I., Lipkin, S., & Shen, X. (2020). Data from: The Cancer Microbiome Atlas (TCMA): A Pan-Cancer Comparative Analysis to Distinguish Organ-Associated Microbiota from Equiprevalent. Duke Research Data Repository. https://doi.org/10.7924/r4rn36833
Hayes, M. C., Gray, P. C., Harris, G., Sedgwick, W. C., Crawford, V. D., Chazal, N., Crofts, S., & Johnston, D. W. (2020). Data from: Drones and deep learning produce accurate and efficient monitoring of large-scale seabird colonies. Duke Research Data Repository. https://doi.org/10.7924/r4dn45v9g
Shindell, D., Zhang, Y., Seltzer, K., Faluvegi, G., Naik, V., Horowitz, L., He, J., Lamarque, J.-F., Sudo, K., & Collins, B. (2020). Data from modeling in support of the Global Methane Assessment, UN Environment, 2020. Duke Research Data Repository. https://doi.org/10.7924/r4qn65b0z
Li, S. & Katul, G. (2020). Data from: Contaminant removal efficiency of floating treatment wetlands. Duke Research Data Repository. https://doi.org/10.7924/r48k7bv5t
Bird, C. N., Duprey, A. H., Dale, J., & Johnston, D. W. (2020). Data and scripts from: A semi-automated method for estimating Adelie penguin colony abundance from a fusion of multispectral and thermal imagery collected with Unoccupied Aircraft Systems. Duke Research Data Repository. https://doi.org/10.7924/r4cv4jq6j
Murphy, S. K., Itchon-Ramos, N., Visco, Z., Huang, Z., Grenier, C., Schrott, R., Acharya, K., Boudreau, M.-H., Price, T. M., Raburn, D. J., Corcoran, D. L., Lucas, J. E., Mitchell, J. T., McClernon, J., Cauley, M., Hall, B. J., Levin, E. D., & Kollins, S. H. (2020). Data from: Cannabinoid exposure and altered DNA methylation in rat and human sperm. Duke Research Data Repository. https://doi.org/10.7924/r4v122j79
Peña, E., Pelot, N. A., & Grill, W. M. (2020). Data from: Quantitative comparisons of block thresholds and onset responses for charge-balanced kilohertz frequency waveforms. Duke Research Data Repository. https://doi.org/10.7924/r4b27wq4m
Kotarba, M., Burgin, A., & Cottrell, K. (2020). Blue Devil Breakdown: enrollment data from 1970 to 2020. Duke Research Data Repository. https://doi.org/10.7924/r4db82p1j
Zhang, Y. (2020). Data from: Contributions of World Regions to the Global Tropospheric Ozone Burden Change from 1980 to 2010. Duke Research Data Repository. https://doi.org/10.7924/r40p13p11
Campbell, L. M., Gray, N., & Gruby, R. (2020). Data from: Q-Sort Concourse and Data for the Human Dimensions of Large MPAs project. Duke Research Data Repository. https://doi.org/10.7924/r4j38sg3b
Berthier, L., Charbonneau, P., & Kundu, J. (2020). Data from: Finite-dimensional vestige of spinodal criticality above the dynamical glass transition. Duke Research Data Repository. https://doi.org/10.7924/r4jh3m094
Fischer, E., Fischer, M., Grass, D., Henrion, I., Warren, W., Westman, E. (2020). Video data files from: Low-cost measurement of facemask efficacy for filtering expelled droplets during speech. Duke Research Data Repository. V2 https://doi.org/10.7924/r4ww7dx6q
Lin, Y., Kouznetsova, T., Chang, C., & Craig, S. (2020). Data from: Enhanced polymer mechanical degradation through mechanochemically unveiled lactonization. Duke Research Data Repository. V2 https://doi.org/10.7924/r4fq9x365
Chavez, S. P., Silva, Y., & Barros, A. P. (2020). Data from: High-elevation monsoon precipitation processes in the Central Andes of Peru. Duke Research Data Repository. V2 https://doi.org/10.7924/r41n84j94
Jeuland, M., Ohlendorf, N., Saparapa, R., & Steckel, J. (2020). Data from: Climate implications of electrification projects in the developing world: a systematic review. Duke Research Data Repository. https://doi.org/10.7924/r42n55g1z
Cardones, A. R., Hall, III, R. P., Sullivan, K., Hooten, J., Lee, S. Y., Liu, B. L., Green, C., Chao, N., Rowe Nichols, K., Bañez, L., Shah, A., Leung, N., & Palmeri, M. L. (2020). Data from: Quantifying skin stiffness in graft-versus-host disease, morphea and systemic sclerosis using acoustic radiation force impulse imaging and shear wave elastography. Duke Research Data Repository. https://doi.org/10.7924/r4h995b4q
Caves, E., Schweikert, L. E., Green, P. A., Zipple, M. N., Taboada, C., Peters, S., Nowicki, S., & Johnsen, S. (2020). Data and scripts from: Variation in carotenoid-containing retinal oil droplets correlates with variation in perception of carotenoid coloration. Duke Research Data Repository. https://doi.org/10.7924/r4jw8dj9h
DiGiacomo, A. E., Bird, C. N., Pan, V. G., Dobroski, K., Atkins-Davis, C., Johnston, D. W., Ridge, J. T. (2020). Data from: Modeling salt marsh vegetation height using Unoccupied Aircraft Systems and Structure from Motion. Duke Research Data Repository. https://doi.org/10.7924/r4w956k1q
Hall, III, R. P., Bhatia, S. M., Streilein, R. D. (2020). Data from: Correlation of IgG autoantibodies against acetylcholine receptors and desmogleins in patients with pemphigus treated with steroid sparing agents or rituximab. Duke Research Data Repository. https://doi.org/10.7924/r4rf5r157
Jin, Y., Ru, X., Su, N., Beratan, D., Zhang, P., & Yang, W. (2020). Data from: Revisiting the Hole Size in Double Helical DNA with Localized Orbital Scaling Corrections. Duke Research Data Repository. https://doi.org/10.7924/r4k072k9s
Kaleem, S. & Swisher, C. B. (2020). Data from: Electrographic Seizure Detection by Neuro ICU Nurses via Bedside Real-Time Quantitative EEG. Duke Research Data Repository. https://doi.org/10.7924/r4mp51700
Yi, G. & Grill, W. M. (2020). Data and code from: Waveforms optimized to produce closed-state Na+ inactivation eliminate onset response in nerve conduction block. Duke Research Data Repository. https://doi.org/10.7924/r4z31t79k
Flanagan, N., Wang, H., Winton, S., Richardson, C. (2020). Data from: Low-severity fire as a mechanism of organic matter protection in global peatlands: thermal alteration slows decomposition. Duke Research Data Repository. https://doi.org/10.7924/r4s46nm6p
Gunsch, C. (2020). Data from: Evaluation of the mycobiome of ballast water and implications for fungal pathogen distribution. Duke Research Data Repository. https://doi.org/10.7924/r4t72cv5v
Warnell, K., & Olander, L. (2020). Data from: Opportunity assessment for carbon and resilience benefits on natural and working lands in North. Carolina. Duke Research Data Repository. https://doi.org/10.7924/r4ww7cd91
Kundu, J., & Charbonneau, P. (2020). Data From: Postponing the dynamical transition density using competing interactions. Duke Research Data Repository. https://doi.org/10.7924/r4xd0wb95
OSNAP is an international program designed to provide a continuous record of the full-water column, trans-basin fluxes of heat, mass and freshwater in the subpolar North Atlantic. The OSNAP observing system consists of two legs: one extending from southern Labrador to the southwestern tip of Greenland across the mouth of the Labrador Sea (OSNAP West), and the second from the southeastern tip of Greenland to Scotland (OSNAP East).
The observing system also includes subsurface floats (OSNAP Floats) in order to trace the pathways of overflow waters in the basin and to assess the connectivity of currents crossing the OSNAP line.
OSNAP is a partner in the North Atlantic Virtual Institute (NAVIS), which connects science teams around the world studying climate variability and change in the North Atlantic. http://navinstitute.org/... [Read More]
The Integrated Precipitation and Hydrology EXperiment (IPHEX) seeks to characterize warm season orographic precipitation regimes, and the relationship between precipitation regimes and hydrologic processes in regions of complex terrain. IPHEX includes two major activities:
1. The development, evaluation and improvement of remote-sensing precipitation algorithms in support of the Global Precipitation Measurement Mission (GPM) through a NASA GPM ground validation field campaign: IPHEX-GVFC (https://iphex.pratt.duke.edu/node/64)
2. The evaluation of Quantitative Precipitation Estimation (QPE) products for hydrologic forecasting and water resource applications in the Upper Tennessee, Catawba-Santee, Yadkin-Pee Dee and Savannah river basins: IPHEX- HAP (H4SE) (https://iphex.pratt.duke.edu/node/65). NOAA HMT has synergy with this project.
How can an amorphous material be rigid? Glass – the prototypical and ubiquitous amorphous solid – inhabits an incredibly ramified and complex energy landscape, which presumably underlies its rigidity. But how? Dealing with so many relevant energy minima and the ensuing far-from-equilibrium dynamics has emerged as one of the central problems in statistical physics. Tackling it requires new tools and concepts. The Simons Collaboration on Cracking the Glass Problem, addressing such fundamental issues as disorder, nonlinear response and far-from-equilibrium dynamics, builds upon three powerful approaches: the study of marginal stability at jamming, the mean-field theory of glasses in infinite dimension, and the dynamics of systems in complex landscapes. The convergence of recent breakthroughs in these areas generates a unique opportunity to come to grips with these three outstanding and intimately related challenges. This collection of datasets is associated with publications from the Charbonneau group and their collaborators as part of the Simons collaboration.
Mitra, S., Zhong, J., MacAlpine, D., Hartemink, A., MacAlpine, H. (2020). Data from: RoboCOP: Multivariate state space model integrating epigenomic accessibility data to elucidate genome-wide chromatin occupancy. Duke Research Data Repository. https://doi.org/10.7924/r4hx1b43s
Cummer, S. A. (2020). Data from: Indirectly measured ambient electric fields for lightning initiation in fast breakdown regions. Duke Digital Repository. https://doi.org/10.7924/r4g44p43t
Ikegami, K., de March, C. A., Nagai, M. H., Ghosh, S., Do, M., Sharma, R., ... Matsunami, H. (2019). Data from: Structural instability and divergence from conserved residues underlie intracellular retention of mammalian odorant receptors. Duke Digital Repository. https://doi.org/10.7924/r40867k2k
Ridge, J. T., Gray, P. C., Windle, A. E., & Johnston, D. W. (2020), Deep learning for coastal resource conservation: automating detection of shellfish reefs. Remote Sens Ecol Conserv. doi:10.1002/rse2.134
Flenner, E., Berthier, L., Charbonneau, P., & Fullerton, C. (2019). Data from: Front-mediated melting of isotropic ultrastable glasses. Duke Digital Repository. https://doi.org/10.7924/r4542pd2c
Liao, M., & Barros, A. P. (2019). The Integrated Precipitation and Hydrology Experiment - Hydrologic Applications for the Southeast US (IPHEX-H4SE) Part IV: High-Resolution Enhanced Stage IV-Raingauge Combined Precipitation Product. Duke Digital Repository. https://idn.duke.edu/ark:/87924/r4pc2zd75
Mremi, A., Broadwater, G., Jackson, K. Amsi, P., Mbulwa, C., Hyslop, T., ... Hall, A. (2019). Data from: Breast cancer in Tanzanian, black American, and white American women: An assessment of prognostic and predictive features, including tumor infiltrating lymphocytes. Duke Digital Repository. https://doi.org/10.7924/r4bv7g09k
Altan, I., James, S., Khan, A., Quinn, M., Charbonneau, P., & McManus, J. (2019). Data and scripts from: Using Schematic Models to Understand the Microscopic Basis for Inverted Solubility in gammaD-crystallin. Duke Digital Repository. https://doi.org/10.7924/r4fq9v942
Huang, O., Long, W., Bottenus, N., Trahey, G., Farsiu, S. Palmeri, M. L. (2019). UltraDuke Version 1. Duke Digital Repository. https://doi.org/10.7924/r49z94h1s
Eghdami, M., & Barros, A. (2019). Namelists and scripts from: Vertical Dependence of Horizontal Scaling Behavior of Orographic Wind and Moisture Fields in Atmospheric Models. Duke Digital Repository. https://doi.org/10.7924/r4154jq8h
Op 't Eynde, J., Yu, A., Eckersley, C., & Bass, C. (2019). Data from: Primary blast wave protection in combat helmet design: a historical comparison between present data and World War I. Duke Digital Repository. https://doi.org/10.7924/r4r49m981
Keating, S., Rountree, W., Grebe, E., Pappas, A. L., Stone, M., Hampton, D.,...Busch, M. P. (2019). Data from: Development of an international external quality assurance program for HIV-1 incidence using the Limiting Antigen Avidity assay. Duke Digital Repository. https://doi.org/10.7924/r4ff3r13q
Khan, A., James, S., Quinn, M., Altan, I., Charbonneau, P., & McManus, J. (2019). Data and scripts from: temperature-dependent interactions explain normal and inverted solubility in a γD-crystallin mutant. Duke Digital Repository. https://doi.org/10.7924/r49w0dx6s
Wilson, J. W., Degan, S., Gainey, C. S., Mitropoulos, T., Simpson, M. J., Zhang, J. Y., & Warren, W. S. (2019). Data from: In vivo pump-probe and multiphoton fluorescence microscopy of melanoma and pigmented lesions in a mouse model. Duke Digital Repository. https://doi.org/10.7924/r4cc0zp95
Duke University Libraries' Multispectral Imaging Team. (2019). [Acts of the Apostles]. (multispectral file stack). Duke Digital Repository. https://doi.org/10.7924/r4c53jx21
Berthier, L., Charbonneau, P., Ninarello, A., Ozawa, M., & Yaida, S. (2019). Data and scripts from: Zero-temperature glass transition in two dimensions. Duke Digital Repository. https://doi.org/10.7924/r46w9b248
Berthier, L., Charbonneau, P., Kundu, J. (2019). Data and scripts from: Bypassing sluggishness: SWAP algorithm and glassiness in high dimensions. Duke Digital Repository. https://doi.org/10.7924/r49w0dr6j
Charbonneau, P., Hu, Y., Raju, A., Sethna, J., & Yaida, S. (2019). Data and scripts from: Morphology of renormalization-group flow for the de Almeida–Thouless–Gardner universality class. Duke Digital Repository. https://doi.org/10.7924/r4zc7wm7d
Charbonneau, P., Corwin, E. I., Fu, L., Tsekenis, G., & van der Naald, M. (2019). Data and scripts from: Glassy, Gardner-like phenomenology in minimally polydisperse crystalline systems. Duke Digital Repository. https://doi.org/10.7924/r4k93500n
Birolo, G., Charbonneau, P., & Hu, Y. (2019). Data and scripts from: Dynamics around the Site Percolation Threshold on High-Dimensional Hypercubic Lattices. Duke Digital Repository. https://doi.org/10.7924/r4571cf37
Altan, I., & Charbonneau, P. (2019). Data and scripts from: Obtaining soft matter models of proteins and their phase behavior. Duke Digital Repository. https://doi.org/10.7924/r4ww7bs1p
River, M. (2019). Data from: Suspended sediment mineralogy in stormflow of the Southern Piedmont. Duke Digital Repository. https://doi.org/10.7924/r4jq0xh5k
Melis, M., Poggi, D., Fasanella, G. O. D., Cordero, S., Katul, G. (2018). Data from: Resistance to flow on a sloping channel covered by dense vegetation following a dam-break. Duke Digital Repository. https://doi.org/10.7924/r4t72c41h
Lyu, F., Cummer, S., Qin, Z., Chen, M. (2018). Data from: Lightning initiation processes imaged with very high frequency broadband interferometry. Duke Digital Repository. https://doi.org/10.7924/r48c9vs2c
