Zobrazeno 1 - 10
of 24 823
pro vyhledávání: '"A, Farris"'
Autor:
Spieker, M., Bazin, D., Biswas, S., Cottle, P. D., Farris, P. J., Gade, A., Ginter, T., Giraud, S., Kemper, K. W., Li, J., Noji, S., Pereira, J., Riley, L. A., Smith, M. K., Weisshaar, D., Zegers, R. G. T.
Publikováno v:
Phys. Rev. C 109, 014307 (2024)
We report new experimental data for excited states of $^{72,74}$Se obtained from proton removal from $^{73,75}$Br secondary beams on a proton target. The experiments were performed with the Ursinus-NSCL Liquid Hydrogen Target and the combined GRETINA
Externí odkaz:
http://arxiv.org/abs/2411.09835
Autor:
Farris, Ashlyn M., Nelson, Michael L.
Mis/disinformation is a common and dangerous occurrence on social media. Misattribution is a form of mis/disinformation that deals with a false claim of authorship, which means a user is claiming someone said (posted) something they never did. We dis
Externí odkaz:
http://arxiv.org/abs/2410.06443
Autor:
Kays, Roland, Snider, Matthew H., Hess, George, Cove, Michael V., Jensen, Alex, Shamon, Hila, McShea, William J., Rooney, Brigit, Allen, Maximilian L., Pekins, Charles E., Wilmers, Christopher C., Pendergast, Mary E., Green, Austin M., Suraci, Justin, Leslie, Matthew S., Nasrallah, Sophie, Farkas, Dan, Jordan, Mark, Grigione, Melissa, LaScaleia, Michael C., Davis, Miranda L., Hansen, Chris, Millspaugh, Josh, Lewis, Jesse S., Havrda, Michael, Long, Robert, Remine, Kathryn R., Jaspers, Kodi J., Lafferty, Diana J. R., Hubbard, Tru, Studds, Colin E., Barthelmess, Erika L., Andy, Katherine, Romero, Andrea, O'Neill, Brian J., Hawkins, Melissa T. R., Lombardi, Jason V., Sergeyev, Maksim, Fisher-Reid, M. Caitlin, Rentz, Michael S., Nagy, Christopher, Davenport, Jon M., Rega-Brodsky, Christine C., Appel, Cara L., Lesmeister, Damon B., Giery, Sean T., Whittier, Christopher A., Alston, Jesse M., Sutherland, Chris, Rota, Christopher, Murphy, Thomas, Lee, Thomas E., Mortelliti, Alessio, Bergman, Dylan L., Compton, Justin A., Gerber, Brian D., Burr, Jess, Rezendes, Kylie, DeGregorio, Brett A., Wehr, Nathaniel H., Benson, John F., O’Mara, M. Teague, Jachowski, David S., Gray, Morgan, Beyer, Dean E., Belant, Jerrold L., Horan, Robert V., Lonsinger, Robert C., Kuhn, Kellie M., Hasstedt, Steven C. M., Zimova, Marketa, Moore, Sophie M., Herrera, Daniel J., Fritts, Sarah, Edelman, Andrew J., Flaherty, Elizabeth A., Petroelje, Tyler R., Neiswenter, Sean A., Risch, Derek R., Iannarilli, Fabiola, van der Merwe, Marius, Maher, Sean P., Farris, Zach J., Webb, Stephen L., Mason, David S., Lashley, Marcus A., Wilson, Andrew M., Vanek, John P., Wehr, Samuel R., Conner, L. Mike, Beasley, James C., Bontrager, Helen L., Baruzzi, Carolina, Ellis-Felege, Susan N., Proctor, Mike D., Schipper, Jan, Weiss, Katherine C. B., Darracq, Andrea K., Barr, Evan G., Alexander, Peter D., Şekercioğlu, Çağan H., Bogan, Daniel A., Schalk, Christopher M., Fantle-Lepczyk, Jean E., Lepczyk, Christopher A., LaPoint, Scott, Whipple, Laura S., Rowe, Helen Ivy, Mullen, Kayleigh, Bird, Tori, Zorn, Adam, Brandt, LaRoy, Lathrop, Richard G., McCain, Craig, Crupi, Anthony P., Clark, James, Parsons, Arielle
Publikováno v:
Diversity and Distributions, 2024 Sep 01. 30(9), 1-16.
Externí odkaz:
https://www.jstor.org/stable/48784956
Purpose: To develop and evaluate a deep learning model for general accelerated MRI reconstruction. Materials and Methods: This retrospective study built a magnetic resonance image processing transformer (MR-IPT) which includes multi-head-tails and a
Externí odkaz:
http://arxiv.org/abs/2405.15098
Deep learning-based MRI reconstruction models have achieved superior performance these days. Most recently, diffusion models have shown remarkable performance in image generation, in-painting, super-resolution, image editing and more. As a generalize
Externí odkaz:
http://arxiv.org/abs/2311.10162
Publikováno v:
Animal Models and Experimental Medicine, Vol 7, Iss 5, Pp 777-780 (2024)
Abstract Streptozotocin (STZ)‐induced type I diabetes mellitus (DM) models have been pivotal in diabetes research due to their ability to mimic the insulin‐dependent hyperglycemia akin to human type I diabetes. However, these models often suffer
Externí odkaz:
https://doaj.org/article/638ac017290d4ee7b31d734f34089bb6
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Deep learning-based MRI reconstruction models have achieved superior performance these days. Most recently, diffusion models have shown remarkable performance in image generation, in-painting, super-resolution, image editing and more. As a g
Externí odkaz:
https://doaj.org/article/29e4065f32754e238fdaa72b7c6cc416
Autor:
Shen, Guoyao, Zhu, Yancheng, Jara, Hernan, Andersson, Sean B., Farris, Chad W., Anderson, Stephan, Zhang, Xin
Recent works have demonstrated success in MRI reconstruction using deep learning-based models. However, most reported approaches require training on a task-specific, large-scale dataset. Regularization by denoising (RED) is a general pipeline which e
Externí odkaz:
http://arxiv.org/abs/2308.10968
Autor:
Wei, Zixiao, Wang, Stanley, Farris, Sean, Chennuri, Naga, Wang, Ningping, Shinsato, Stara, Demir, Kahraman, Horii, Maya, Gu, Grace X.
As natural predators, owls fly with astonishing stealth due to the sophisticated serrated surface morphology of their feathers that produces advantageous flow characteristics and favorable boundary layer structures. Traditionally, these serrations ar
Externí odkaz:
http://arxiv.org/abs/2308.08788
Autor:
Shen, Guoyao, Hao, Boran, Li, Mengyu, Farris, Chad W., Paschalidis, Ioannis Ch., Anderson, Stephan W., Zhang, Xin
The application of compressed sensing (CS)-enabled data reconstruction for accelerating magnetic resonance imaging (MRI) remains a challenging problem. This is due to the fact that the information lost in k-space from the acceleration mask makes it d
Externí odkaz:
http://arxiv.org/abs/2306.12365