Zobrazeno 1 - 10
of 600
pro vyhledávání: '"Beroza, P."'
Autor:
McBrearty, Ian W., Beroza, Gregory C.
Double difference earthquake relocation is an essential component of many earthquake catalog development workflows. This technique produces high-resolution relative relocations between events by minimizing differential measurements of the arrival tim
Externí odkaz:
http://arxiv.org/abs/2410.19323
In this work, we introduce AutoFragDiff, a fragment-based autoregressive diffusion model for generating 3D molecular structures conditioned on target protein structures. We employ geometric vector perceptrons to predict atom types and spatial coordin
Externí odkaz:
http://arxiv.org/abs/2401.05370
Autor:
Alenna J Beroza, Sarah Rine, Jean C Bikomeye, Resty Kyomukama Magezi, Ouma Simple, Julia Dickson-Gomez, Macklean Mary Kyomya, Dan Katende, Matida Bojang, Wamala Twaibu, Fiona Mutesi Magololo, Agnes Nyabigambo, Geofrey Musinguzi, Pius Mulamira, Kirsten Beyer
Publikováno v:
Journal of Global Health Reports, Vol 8 (2024)
# Background Global initiatives have emphasized the elimination of cervical cancer (CC) among female sex workers (FSW) in Africa. Yet screening remains low, and few interventions have been outlined to target this group. This scoping review sought to
Externí odkaz:
https://doaj.org/article/92c2265c6a2f425c927a28579008776f
Autor:
McBrearty, Ian W., Beroza, Gregory C.
Publikováno v:
Bulletin of the Seismological Society of America (2023)
Seismic phase association connects earthquake arrival time measurements to their causative sources. Effective association must determine the number of discrete events, their location and origin times, and it must differentiate real arrivals from meas
Externí odkaz:
http://arxiv.org/abs/2209.07086
Autor:
Zhu, Weiqiang, Hou, Alvin Brian, Yang, Robert, Datta, Avoy, Mousavi, S. Mostafa, Ellsworth, William L., Beroza, Gregory C.
Earthquake monitoring workflows are designed to detect earthquake signals and to determine source characteristics from continuous waveform data. Recent developments in deep learning seismology have been used to improve tasks within earthquake monitor
Externí odkaz:
http://arxiv.org/abs/2208.14564
Autor:
McBrearty, Ian W., Beroza, Gregory C.
Publikováno v:
2022 IEEE International Conference on Image Processing (ICIP)
We solve the traditional problems of earthquake location and magnitude estimation through a supervised learning approach, where we train a Graph Neural Network to predict estimates directly from input pick data, and each input allows a distinct seism
Externí odkaz:
http://arxiv.org/abs/2203.05144
Earthquake monitoring by seismic networks typically involves a workflow consisting of phase detection/picking, association, and location tasks. In recent years, the accuracy of these individual stages has been improved through the use of machine lear
Externí odkaz:
http://arxiv.org/abs/2109.09911
Autor:
Zhu, Weiqiang, McBrearty, Ian W., Mousavi, S. Mostafa, Ellsworth, William L., Beroza, Gregory C.
Earthquake phase association algorithms aggregate picked seismic phases from a network of seismometers into individual earthquakes and play an important role in earthquake monitoring. Dense seismic networks and improved phase picking methods produce
Externí odkaz:
http://arxiv.org/abs/2109.09008
Autor:
G. Kwiatek, P. Martínez-Garzón, D. Becker, G. Dresen, F. Cotton, G. C. Beroza, D. Acarel, S. Ergintav, M. Bohnhoff
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-10 (2023)
Abstract Short term prediction of earthquake magnitude, time, and location is currently not possible. In some cases, however, documented observations have been retrospectively considered as precursory. Here we present seismicity transients starting a
Externí odkaz:
https://doaj.org/article/7263ab44a18c473bb2112ecd4bbeddc0
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-9 (2023)
Abstract Water scarcity is a pressing issue in California. We develop ambient noise differential adjoint tomography that improves the sensitivity to fluid-bearing rocks by canceling bias caused by noise sources. Here we image the shallow S-wave veloc
Externí odkaz:
https://doaj.org/article/779fa68777684ba6a323cc85958e19ff