Dataset Information

Newmark displacement data for low to moderate magnitude events in the Betic Cordillera.

ABSTRACT: Land-use decisions in relation to seismic-induced landslide hazard are usually made through the preparation of hazard maps. The rigid-block method is probably the most used for this purpose. Under this method, Newmark displacement is computed for each slope unit and this displacement is used as a guide for establishing categories of hazard. At present, most relations used for computing Newmark displacement are established from moderate-to-high magnitude earthquakes (Mw ? 6.5). This data article provides Newmark displacements computed from accelerograms recorded in the Betic Cordillera for low-to-moderate magnitude earthquakes (Mw?=?3.5-6.3). Records come from the Spanish Strong Ground Motion database (Instituto Geográfico Nacional). Newmark displacements were computed focusing on yield accelerations frequently recorded in such scenarios (0.02, 0.03, 0.04, 0.05, 0.06, 0.08 and 0.10), although higher accelerations were also considered (0.125, 0.15, 0.20, 0.25 and 0.30 g's). These data are useful for the study of the hazard in seismic scenarios of low-to-moderate magnitude, very frequent in practice. These data have been used in the study by Delgado et al. [1].

SUBMITTER: Delgado J

PROVIDER: S-EPMC7415828 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Newmark displacement data for low to moderate magnitude events in the Betic Cordillera.

Delgado José J Rosa Julio J Peláez José A JA Rodríguez-Peces Martín J MJ Garrido Jesús J Tsigé Meaza M

Data in brief 20200731

Land-use decisions in relation to seismic-induced landslide hazard are usually made through the preparation of hazard maps. The rigid-block method is probably the most used for this purpose. Under this method, Newmark displacement is computed for each slope unit and this displacement is used as a guide for establishing categories of hazard. At present, most relations used for computing Newmark displacement are established from moderate-to-high magnitude earthquakes (Mw ≥ 6.5). This data article ...[more]

PMID: 32793783

Similar Datasets

Project description:Despite the proliferation of deep learning techniques for accelerated MRI acquisition and enhanced image reconstruction, the construction of large and diverse MRI datasets continues to pose a barrier to effective clinical translation of these technologies. One major challenge is in collecting the MRI raw data (required for image reconstruction) from clinical scanning, as only magnitude images are typically saved and used for clinical assessment and diagnosis. The image phase and multi-channel RF coil information are not retained when magnitude-only images are saved in clinical imaging archives. Additionally, preprocessing used for data in clinical imaging can lead to biased results. While several groups have begun concerted efforts to collect large amounts of MRI raw data, current databases are limited in the diversity of anatomy, pathology, annotations, and acquisition types they contain. To address this, we present a method for synthesizing realistic MR data from magnitude-only data, allowing for the use of diverse data from clinical imaging archives in advanced MRI reconstruction development. Our method uses a conditional GAN-based framework to generate synthetic phase images from input magnitude images. We then applied ESPIRiT to derive RF coil sensitivity maps from fully sampled real data to generate multi-coil data. The synthetic data generation method was evaluated by comparing image reconstruction results from training Variational Networks either with real data or synthetic data. We demonstrate that the Variational Network trained on synthetic MRI data from our method, consisting of GAN-derived synthetic phase and multi-coil information, outperformed Variational Networks trained on data with synthetic phase generated using current state-of-the-art methods. Additionally, we demonstrate that the Variational Networks trained with synthetic k-space data from our method perform comparably to image reconstruction networks trained on undersampled real k-space data.

Dataset Information

Newmark displacement data for low to moderate magnitude events in the Betic Cordillera.

Publications

Newmark displacement data for low to moderate magnitude events in the Betic Cordillera.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets