Probabilistic Seismic Hazard Analysis Using Stochastic Simulated Ground Motions

In recent years, ground motion models used in probabilistic seismic hazard analyses have evolved from the traditional approach of using ground motion prediction equations (GMPEs) to using ground motion time series models. The purpose of this paper is to develop an approach to perform a probabilistic seismic hazard analysis using stochastic site-based simulation techniques. These techniques consist of empirical stochastic models that simulate both near-fault and far-field ground motion time series. The near-fault models consider directivity pulses, which can impose large seismic demands. The proposed approach was applied to a site located in downtown Los Angeles, California, and the corresponding hazard curves were developed. The results were compared to hazard curves derived for the same site from CyberShake, which uses a physics-based simulation approach, and from a traditional GMPE approach. The comparison indicated that the proposed methodology accurately describes the seismic hazard at the site at high hazard levels. The proposed approach is computationally efficient compared to the use of physics-based simulations like CyberShake.The authors are grateful to Kevin Milner, Scott Callaghan, and Rob Graves for answering our questions about the CyberShake platform

Stochastic simulation of earthquake ground motions for the seismic assessment of monumental masonry structures: source-based vs site-based approaches

Earthquakes are among the most destructive natural disasters and have resulted in a massive number of fatalities and economic losses all over the world. Simulated ground motion records are valuable, particularly for regions lacking seismic stations or with a limited history of large-magnitude earthquakes. Notably, a significant percentage of monumental masonry buildings are located in regions with limited access to real records; hence, simulated records play a paramount role in their seismic protection. However, few studies have investigated the structural response of heritage buildings via response history analyses to assess the performance of simulated earthquakes against real ones. To accomplish this, this study simulates the recorded time-series of the 9th of July 1998 Faial earthquake in the Azores (Mw = 6.2) at four available stations, using two different simulation approaches, that is, a source-based stochastic finite-fault method and a site-based broadband stochastic method. First, two masonry facades with sidewalls characterized by different slenderness levels are adopted to conduct this research. Moreover, the proposed approach is also applied to an existing monumental structure, that is, São Francisco Church, located at Horta, which was affected by damage during the Faial earthquake. Results demonstrate that both simulation approaches provide similar results in terms of structural response prediction. The proposed framework also demonstrates that a small mismatch in terms of predicted damage patterns can result in a significant relative error in terms of displacement predictions.This work was partly financed by FCT/MCTES through national funds (PIDDAC) under the R&D Unit ISISE under refer ence UIDB/04029/2020, and under the Associate Laboratory Advanced Production and Intelligent Systems ARISE under reference LA/P/0112/2020. This study has been partly funded by the STAND4HERITAGE project that has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Grant agreement No. 833123), as an Advanced Grant. This work is also partly financed by MPP2030-FCT PhD Grants under the R&D Unit Insti-tute for Sustainability and Innovation in Structural Engineering (ISISE), under reference PRT/BD/154348/2022. This work is partly financed by national funds through FCT—Foundation for Science and Technology, under grant agreement UI/BD/153379/2022 attributed to the 4th author. This study has been partly funded by Foundation of Science and Technology, under grant agreement PRT/BD/154348/2022

Aortic Valve Area and Strain Measurements by Cardiac MRI and Transthoracic Echocardiography in Severe Aortic Stenosis with Normal Left Ventricular Function

Background: Transthoracic echocardiography (TTE) is the recommended imaging technique for the evaluation of patients with aortic stenosis (AS). However, in cases with inconclusive findings, cardiac magnetic resonance (CMR) planimetry is used to grade AS severity. This study aimed to compare the results derived from TTE and CMR in patients with severe AS with normal left ventricular (LV) function.Methods: In a prospective study, 20 patients with severe AS were recruited and data derived from TTE and CMR modalities were compared with the archived records of 28 age- and sex-matched healthy controls. The data included aortic valve area (AVA), MRI-derived biventricular global strains, and TTE-derived global longitudinal strain (GLS). SPSS software was used to analyze the data with independent samples t test, intraclass correlation coefficient (ICC), and Pearson correlation. P<0.05 was considered statistically significant.Results: An excellent agreement was found in AVA values derived from CMR and TTE with an average ICC of 0.932 (95% CI=0.829-0.973). There was a significant difference in LV-GLS, LV global radial strain (GRS), right ventricular (RV) GRS, and RV global circumferential strain between the groups. A good correlation was found between CMR- and TTE-derived GLS with an average ICC of 0.721 (95% C=0.255-0.896). The mean aortic valve pressure gradient in TTE had a significant inverse linear correlation with LV-GRS in CMR (r=-0.537). All P values were <0.05.Conclusion: There was a good agreement between AVA and strain values derived from cardiac MRI and TTE. The myocardial strain was impaired in patients with severe AS and normal LV function and correlated with disease severity

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

Stochastic Modeling and Simulation of Ground Motions for Performance-Based Earthquake Engineering

A site-based fully-nonstationary stochastic model for strong earthquake ground motion is developed. The model employs filtering of a discretized whit-noise process. Nonstationarity is achieved by modulating the intensity and varying the filter properties in time. The formulation has the important advantage of separating the temporal and spectral nonstationary characteristics of the process, thereby allowing flexibility and ease in modeling and parameter estimation. The model is fitted to recorded ground motions by matching a set of statistical characteristics, including the mean-square intensity, the mean zero-level up-crossing rate, and a measure of the bandwidth, all expressed as functions of time. These characteristics represent the evolving intensity and time-varying frequency content of the ground motion. Post-processing by a second filter assures zero residual velocity and displacement, and improves the match to response spectral ordinates for long periods.The proposed stochastic model is employed to develop a method for generating an ensemble of synthetic ground motion time-histories for specified earthquake and site characteristics. The stochastic model is fitted to a large number of recorded ground motions taken from the PEER NGA database. Strong ground motions recorded on firm ground with source-to-site distance of at least 10 km are selected. Fitting to recorded ground motions results in sample observations of the stochastic model parameters. Using this sample, predictive equations are developed for the model parameters in terms of the faulting mechanism, earthquake magnitude, source-to-site distance and the site shear-wave velocity. For any specified set of these earthquake and site characteristics, sets of the model parameters are generated, which are in turn used in the stochastic model to generate an ensemble of synthetic ground motions. The resulting synthetic accelerations as well as corresponding velocity and displacement time-histories capture the main features of real earthquake ground motions, including the intensity, duration, spectral content, and peak values. Furthermore, the statistics of their resulting elastic response spectra closely agree with both the median and the variability of response spectra of recorded ground motions, as reflected in existing prediction equations based on the NGA database. The proposed method can be used in seismic design and analysis in conjunction with or instead of recorded ground motions.The method of ground motion simulation for specified earthquake and site characteristics is extended to simulate orthogonal horizontal ground motion components. Two stochastic processes are considered, each representing one component. Assuming statistical independence between the underlying white-noise processes, the two horizontal components are simulated on a set of orthogonal principal axes, along which the components are statistically uncorrelated. A database of principal component ground motion pairs is developed by rotating the as-recorded horizontal ground motion component pairs into their principal axes. The stochastic model is fitted to the recorded motions in the principal component database. Using the resulting sample observations for the model parameters, regression models are developed to empirically relate each model parameter to the earthquake and site characteristics. Correlations between parameters of the two ground motion components are empirically determined. Given earthquake and site characteristics, the results of this study allow one to generate realizations of correlated model parameters for the two horizontal ground motion components. Each set of these model parameter realizations along with two statistically independent white-noise processes are used in the stochastic model to generate an orthogonal pair of horizontal ground motion components along the principal axes. The simulated components, while being statistically independent, have overall characteristics, i.e., evolution of intensity and frequency content, that are similar to each other in the same way that the characteristics of a pair of real recorded ground motion components along their principal axes are similar. The simulated principal components may be rotated into any desired direction, such as the coordinate axes of a structure, through a simple orthogonal transformation

Effect of Nasal Spray on the Treatment of Chronic Rhinosinusitis Without a Nasal Polyp

Background Chronic rhinosinusitis (CRS) is a common inflammatory disease of nasal and paranasal sinuses, with many treatment methods available for the management of this disease. Recently, herbal medicines have shown a significant impact on inflammatory diseases such as CRS, and one of these herbal medicines is Nigella sativa . Therefore, the current study aimed to evaluate the effectiveness of N. sativa in patients with CRS without nasal polyp (CRSsNP). Methods In this randomized clinical trial, 65 patients with mild to moderate CRSsNP were enrolled based on the inclusion criteria. Patients were divided randomly into 2 parallel groups: intervention and placebo groups. Patients in the intervention group received 2 puffs/day of N. sativa nasal spray (1 g/day of N. sativa ) and in the placebo group received 2 puffs/day of sodium chloride spray 0.65%. Results Thirty-one patients (19 men and 12 women) in the intervention group and 34 in the placebo group (18 men and 16 women) were evaluated. Lund–McKay, Lund Kennedy, and Sino-Nasal Outcome Test-22 scores were assessed for both groups after 8 weeks of treatments. These scores decreased significantly in both groups. However, these scores were significantly lower in the intervention group compared with the placebo group ( P  < .0001, for all). Conclusion The use of N. sativa nasal spray has symptom reliever effect with no adverse effects in patients with CRSsNP

Simulation of earthquake ground motions in the eastern U. S. using deterministic physics-based and stochastic approaches

Earthquake ground motion recordings are scarce in the central and eastern U.S. (CEUS) for large magnitude events and at close distances. We use two different simulation approaches, a deterministic physics-based model and a stochastic model, to simulate recordings from the 2011 Mineral, Virginia, 5.8 earthquake in the CEUS. We then use the 2001 Bhuj, India, 7.6 earthquake as a tectonic analog for a large CEUS earthquake and modify our simulations to develop models for generation of large magnitude earthquakes in the CEUS. Both models show a good fit to the observations from 0.1 to 10 Hz, and show a faster fall-off with distances beyond 500 km for the acceleration spectra compared to ground motion prediction models (GMPEs) for a 7.6 event.Non UBCUnreviewedThis collection contains the proceedings of ICASP12, the 12th International Conference on Applications of Statistics and Probability in Civil Engineering held in Vancouver, Canada on July 12-15, 2015. Abstracts were peer-reviewed and authors of accepted abstracts were invited to submit full papers. Also full papers were peer reviewed. The editor for this collection is Professor Terje Haukaas, Department of Civil Engineering, UBC Vancouver.Othe

Lessons Learned from a Decade of Ground Motion Simulation Validation (GMSV) Exercises and a Path Forward

Simulated ground motions can advance seismic hazard and structural response analyses, particularly for conditions with limited recorded ground motions, such as large magnitude earthquakes at short source-to-site distances. Rigorous validation of simulated ground motions is required before regulatory bodies, practicing engineers, or hazard analysts can be confident in their use. A decade ago, validation exercises were mainly limited to comparisons of simulated to observed waveforms and median values of spectral accelerations. The Southern California Earthquake Center (SCEC) Ground Motion Simulation Validation (GMSV) group was formed to increase coordination among simulation modelers and research engineers with the aim of devising and applying effective methods for simulation validation. Here, we categorize alternate validation methods according to their approach and the metrics considered. Two general validation approaches are to compare various metrics from simulations to their counterparts from historical records or to their estimated values from existing empirical models. Validation metrics consist of ground motion characteristics and structural responses. We describe this categorization, provide examples that have been valuable in the past decade, and provide potential research directions. Key lessons learned by our GMSV group are that validation is application specific, our outreach and communication warrants improvement, and much research remains unexplored

Estimation of Ground Motion Variability in the CEUS Using Simulations

We estimate earthquake ground-motion variability in the central and eastern U.S. (CEUS) by varying the model parameters of a deterministic physics-based and a stochastic site-based simulation method. Utilizing a moderate-magnitude database of recordings, we simulate ground motions for largermagnitude scenarios M6.0, 6.5, 7.0, 7.5, and 8.0. For the physics-based method, we vary the faulting mechanism, slip, stress drop, rupture velocity, source depth, and 1D velocity structure. For the stochastic method, we simulate realizations using a set of six model parameters, each of which has a preassigned probability distribution. The median spectral accelerations over all synthetic realizations are compared with the NGA-East models. The synthetic standard deviation for deterministic simulations ranges from approximately 0.4 to 0.85 for various magnitudes and distances, whereas that for stochastic simulations is between 0.48 and 1.04. Based on the simulation results and comparisons with NGA-East variability models, a range for ground motion variability in the CEUS is discussed