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Performance for three independent living tasks were examined via task analyses. Given the relatively small sample size (n = 56) of individuals with intellectual and developmental disabilities, we simulated 1000 replications based upon observed results using Monte Carlo techniques. The results of the current study suggest that: (1) adaptive behavior was more related to task performance than IQ; and (2) after statistically controlling for adaptive behavior, task performance was influenced by the first step. Task performance appear to be over‐estimated with the inclusion of the first step. [ABSTRACT FROM AUTHOR]

Background: Previous research has shown that post‐secondary collegiate vocational educational programs often have positive effects on employment outcomes for young adults with intellectual and developmental disabilities. Aims: Using secondary data of a program in the United States collected over several years, we examined which intervention components of a postsecondary education transition program predicted subsequent employment for young adults with intellectual and developmental disabilities. Materials & Methods: The sample consisted of 56 individuals that participated in a transition‐services collegiate program; Crossing Points, University of Alabama. Results: Results were able to robustly indicate that acquiring job‐specific skills was a much better predictor than global measures of intellectual or adaptive behaviour. Additionally, survival curve analyses as an innovative approach to this population showed that there was a positive relation between the number of job‐specific training sessions and eventual community employment. Discussion: Results are discussed in relation to a historical parallel movement to expand inclusion of students with intellectual and developmental disabilities in the least restrictive educational setting for primary and secondary public education years. Conclusion: In conclusion, the results of the current study suggest positive findings with job‐skills training both specific and general. [ABSTRACT FROM AUTHOR]

Over the past 15 years and through multiple large and devastating earthquakes, tsunami warning systems have grown considerably in their efficacy in providing timely and accurate forecasts to affected communities. However, one part of tsunami warning that still needs improvement is forecasts catered to local, near‐field communities in the time after an earthquake rupture but before coastal inundation. In this study, we test a rapid, Global Navigation Satellite Systems (GNSS)‐driven earthquake characterization model using a large data set of synthetic megathrust ruptures for its near‐field tsunami forecasting potential. We also provide a framework for tsunami forecasting that focuses on the likelihood of exceedance of user‐defined coastal amplitudes that may be of use in the first 15 min following an earthquake. Specifically, we can estimate the earthquake magnitude, without saturation, for 82% of tested ruptures. We can also identify test ruptures as dominantly thrust events, without analyst guidance for 92% of tested thrust ruptures. Finally, modeling the tsunami component of our rapidly estimated fault rupture leads to greater than 80% accuracy in identifying tsunami impact at key coastal amplitude thresholds. This is promising for near‐field warning when the time prior to inundation is limited to tens of minutes. We focus this study on large megathrust ruptures along the quiescent Cascadia subduction zone where there is already a dense GNSS network. Key Point: Local GNSS is a useful tool in near‐field tsunami hazard analysis [ABSTRACT FROM AUTHOR]

Historical records have proven that the southern coasts of Java, Indonesia, are prone to tsunamis. The existing tsunami observing system using bottom pressure gauges, also known as tsunameters, composes a global network but is too sparse for regional tsunami forecasts. The nearest tsunameter to Indonesia is located approximately 500‐km offshore, which is not very useful for the area, particularly for a tsunami source in eastern part of the Sunda megathrust. Here we propose a methodology to optimally place offshore tsunameters with the main consideration of operational costs, which is proportional to the number of observation points. We use a stochastic slip model of earthquakes with Mw 8.8–9.2 to generate multiple tsunami source realizations representing possible future events in the region. Based on the sources, we then identify a potential zone where an early tsunami detection is feasible. Furthermore, empirical orthogonal functions derived from tsunami simulations are used to determine the initial locations for tsunameter placement inside the specified zone. Finally, we apply an optimization scheme to improve the initial locations that facilitates both tsunami forecasts and source characterizations through a tsunami waveform inversion analysis. Our result indicates that six tsunameters are sufficient to efficiently cover the major seismogenic region in the study area. Key Points: The study proposes an efficient design of tsunami observation network off southern coast of Java, IndonesiaWe utilize optimizations to determine the best observation locations for multiple earthquake models (Mw 8.8‐9.2)The result suggests locations of six tsunameters that can provide accurate tsunami forecasts and source characterizations [ABSTRACT FROM AUTHOR]

Finite‐fault inversions are a common technique, employed following large earthquakes, used to understand the nature of slip along a fault. Using multiple data sets, including static offsets from geodetic instruments and tsunami wave heights from open‐ocean gauges, a richer perspective on the expected slip distribution than using a singular tool is created. However, the model resolution obtained from open‐ocean tsunami data and techniques used to subsample that data have not been widely evaluated. Static geodetic data can provide near‐complete model resolution of the subduction megathrust near the trench, if data are local. However, model resolution falls off precipitously as distance between instrument and fault increases when geodetic data are limited to more distal on‐land sites. Tsunami data derived from open‐ocean waveforms are less dependent on station to fault distance, but offshore model resolution is lost due to necessary data processing, such as windowing, often necessary to avoid coastal reflections. This primarily affects the resolution in the downdip direction, which often arrives at open‐ocean stations later in the waveform. Spatial detail is also limited by the minimum subfault size that will satisfy the longwave approximation, which is dependent on the water depth. For most cases, this subfault limit is approximately 20 by 20 km. In many environments, the sparsity of offshore geodetic instruments, and the large distances between estimated slip and coastal geodetic gauges, makes the inclusion of open‐ocean data, if available, highly advantageous. Still it is possible even with the pairing of on‐land and offshore data sets for poorly resolved zones to exist. In these cases further resolution can be recovered through the incorporation of additional data sets such as strong‐motion data and seismic waveforms through a seismic‐geodetic inversion. Key Points: We quantify loss of offshore model resolvability from on‐land static geodetic data sets along a megathrustTsunami waveform data sets are more sensitive to offshore slip—so long as the data are not contaminated with poorly constrained effects such as coastal reflections [ABSTRACT FROM AUTHOR]