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
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
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
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
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.
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
Teti, Z., & Blumsack, S. (2021). RTOGov: regional transmission organization member voting data. Duke Research Data Repository. https://doi.org/10.7924/r40k2dx36
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
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
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
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
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
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
Lam, C. T., Krieger, M. S., Gallagher, J. E., Asma, B., Schmitt, J. W, & Ramanujam, N. (2015). Data from: Design of a novel low cost point of care tampon (POCkeT) colposcope for use in resource limited settings. Duke Digital Repository. http://hdl.handle.net/10161/10056
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
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
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
Warnell, K., & Olander, L. (2021). Pocosin wetland status and owner type for North Carolina. Duke Research Data Repository. https://doi.org/10.7924/r4s75fc6q
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
Smith, H. A., & Garomsa, B. (2021). Data and scripts from: Rubenstein Library card catalog. Duke Research Data Repository. https://doi.org/10.7924/r4br8v905
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
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
Lozier, M.S., F. Li, S. Bacon, F. Bahr, A.S. Bower, S.A. Cunningham, M.F. de Jong, L. de Steur, B. deYoung, J. Fischer, S.F. Gary, B.J.W. Greenan, N.P. Holliday, A. Houk, L. Houpert, M.E. Inall, W.E. Johns, C. Johnson, J. Karstensen, G. Koman, I.A. Le Bras, X. Lin, N. Mackay, M. Oltmanns, R.S. Pickart, A.L. Ramsey, D. Rayner, F. Straneo, D.J. Torres, I. Yashayaev, J. Zhao (2019). Meridional overturning circulation and the associated heat and freshwater transports observed by the OSNAP (Overturning in the Subpolar North Atlantic Program) Array from 2014 to 2016. Duke Digital Repository. https://doi.org/10.7924/r4z60gf0f
Schaffer-Smith, D., Swenson, J. J. (2018). Data and scripts from: Migratory shorebird response to non-tidal wetland dynamics at an internationally important inland Pacific Flyway stopover. Duke Digital Repository. https://doi.org/10.7924/r47w6b882
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 drones. Duke Research Data Repository. V2 https://doi.org/10.7924/r4sj1jj6s
Charbonneau, P. & Hu, Yi. (2021). Data and scripts accompanying comment on: "Kosterlitz-Thouless-type caging-uncaging transition in a quasi-one-dimensional hard disk system". Duke Research Data Repository. https://doi.org/10.7924/r4g16258z
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, B., Charbonneau, P., Szamel, G. (2018). Data from: A microscopic model of the Stokes-Einstein Relation in arbitrary dimension. Duke Digital Repository. https://doi.org/10.7924/r4x061q6f
Berthier, L.; Charbonneau, P.; Flenner, E.; Zamponi, F. (2017). Data and scripts from: The origin of ultrastability in vapor-deposited glasses. Duke Digital Repository. https://doi.org/10.7924/G8P26W5G
Charbonneau, P., Li, Y. (C.), Pfister, H. D., & Yaida, S. (2017). Cycle-expansion method for the Lyapunov exponent, susceptibility, and higher moments. Duke Digital Repository. https://doi.org/10.7924/G88050N6