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Following an earthquake, ground motion time series are needed to carry out site-specific nonlinear response history analysis. However, the number of currently available recording instruments is sparse; thus, the ground motion time series at uninstrumented sites must be estimated. Tamhidi et al. developed a Gaussian process regression (GPR) model to generate ground motion time series given a set of recorded ground motions surrounding the target site. This GPR model interpolates the observed ground motions’ Fourier Transform coefficients to generate the target site’s Fourier spectrum and the corresponding time series. The robustness of the optimized hyperparameter of the model depends on the surrounding observation density. In this study, we carried out sensitivity analysis and tuned the hyperparameter of the GPR model for various observation densities. The 2019 M7.1 Ridgecrest and 2020 M4.5 South El Monte earthquake data sets recorded by the Community Seismic Network and California Integrated Seismic Network in Southern California are used to demonstrate the process. To provide a tool to quantify the uncertainty of the generated motions, a methodology to develop realizations of ground motion time series is also incorporated. The results illustrate that the uncertainty of the generated motions is lower at longer periods. It is shown that the observation density in the proximity of the target site plays a vital role in both error and uncertainty reduction of the generated time series. To demonstrate the concept, the effect of additional observations from combined recording networks is investigated.

Bicycling for transportation and recreation has many benefits including human health, greenhouse gas reduction, and community building. Understanding the factors that influence intentions to bicycle can help community planners improve access to bicycle routes and facilities for residents. This study examines the facilitators, constraints, motivations, demographic and experiential characteristics, and intentions to ride a bicycle of the residents of the Town of DeWitt in Central New York State. Data were collected using a mail and internet survey during the summer of 2015. Survey questions focused on constraints/facilitators, motivations, intentions, demographics, recent participation in bicycling during the summer of 2015, and lifetime involvement in bicycling (i.e., number of years). Of the 1,253 questionnaires distributed, a qualified sample of 1,206 households was obtained; 56 questionnaires were completed online and 417 were returned by mail, resulting in a 39% response rate. Descriptive statistics and path analysis were used to identify determinants of bicycling intentions. Lack of adequate infrastructure was identified as a significant constraint on bicycling intentions, while support for infrastructure enhancements, enjoyment from riding, riding to spend time with friends and family, and number of children in the respondent’s household all directly and significantly influenced intentions to bike ride. Other factors (i.e., infrastructure connections in the community, spending time outdoors, support from others for biking, gender, free time, age, and income) indirectly influenced intentions. The results indicate that respondents would likely be in support of infrastructure improvements in the future, especially if these improvements create safer riding locations for both adults and children. In addition, the analysis made it possible to discern previously unrecognized factors influencing bicycling intentions, such as gender-based differences in level of support for biking infrastructure enhancements, the number of children in the household, and the importance of biking as a social experience. Incorporating off-road bike paths and gathering places for bicyclists into future planning efforts would likely be supported by residents seeking safe riding experiences for themselves and their children.

We describe source and path attributes of the Next Generation of Ground-Motion Attenuation for Subduction zones (NGA-Sub) project relational database. The database contains 991 earthquakes between 1937 and 2016 that meet quality assurance standards and have assigned event types (mostly interface or intraslab). Data curation emphasized large magnitudes: 73% of events have M > 5 and 13 events have M > 8. Event attributes in the database can be broadly divided into those related to the moment tensor, those related to rupture surface geometry (referred to as finite-fault parameters), and categorizations by type (e.g. interface, intraslab) and sequence classification (mainshock, aftershock). Earthquake information and moment tensor parameters compiled from earthquake catalogs include event date and origin time, hypocenter location, seismic moment, and the strike, dip, and rake angles of nodal planes. Finite-fault parameters include along-strike length, down-dip width, and depth to top-of-rupture for one or more rectangles used to parameterize rupture surface geometry. These are modified from models in literature where available, and otherwise are simulated using procedures customized for subduction earthquakes. Rupture distance and other metrics are computed using finite-fault representations of sources, and (as applicable) are partitioned into forearc and backarc components. Forearc and backarc regions are defined based on volcano locations, and are assigned to events and sites.

This Medical News article discusses a new report from the US Centers for Disease Control and Prevention on maternal deaths during and up to a year after pregnancy, racial disparities, and new models of care aimed at reducing maternal mortality.

This Medical News article discusses a trend of gabapentin misuse and harms, including fatal overdoses.

This Medical News article discusses a movement to allow adequate family and medical leave for physicians in training.

This Medical News article discusses US initiatives to improve health care worker well-being as burnout and intent to leave to medicine reach record levels.