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Abstract Despite significant study, when and how plate tectonics initiated on Earth remains contentious. Geologic evidence from some of Earth's earliest cratons has been interpreted as reflecting the formation of initial continental blocks by non‐subduction processes, which then trigger subduction initiation at their margins. Numerical models of mantle convection with a plastic yield stress rheology have shown this scenario is plausible. However, whether continents can trigger subduction initiation has not been tested with other rheologies. We, therefore, use numerical models of mantle convection with an imposed continental block to test whether continents facilitate subduction initiation with a grain‐damage mechanism, where weak shear zones form by grain size reduction. Our results show that continents modestly enhance stresses in the lithosphere, but not enough to significantly impact lithospheric damage or subduction initiation: continents have minimal influence on lithospheric damage or plate speed, nor does subduction preferentially initiate at the continental margin. A new regime diagram that includes continental blocks shows only a small shift in the boundary between the mobile‐lid and stagnant‐lid regimes when continents are added. However, as we do find that stresses are modestly enhanced at the continental margin in our models, we develop a scaling law for this stress enhancement to more fully test whether continents could trigger subduction initiation on early Earth. We find that lithospheric stresses supplied by continents are not sufficient to initiate subduction on the early Earth on their own with grain‐damage rheology; instead, additional factors would be required. 

Predicting future walking joint kinematics is crucial for assistive device control, especially in variable walking environments. Traditional optical motion capture systems provide kinematics data but require laborious post-processing, whereas IMU based systems provide direct calculations but add delays due to data collection and algorithmic processes. Predicting future kinematics helps to compensate for these delays, enabling the system real-time. Furthermore, these predicted kinematics could serve as target trajectories for assistive devices such as exoskeletal robots and lower limb prostheses. However, given the complexity of human mobility and environmental factors, this prediction remains to be challenging. To address this challenge, we propose the Dual-ED-Attention-FAM-Net, a deep learning model utilizing two encoders, two decoders, a temporal attention module, and a feature attention module. Our model outperforms the state-of-the-art LSTM model. Specifically, for Dataset A, using IMUs and a combination of IMUs and videos, RMSE values decrease from 4.45° to 4.22° and from 4.52° to 4.15°, respectively. For Dataset B, IMUs and IMUs combined with pressure insoles result in RMSE reductions from 7.09° to 6.66° and from 7.20° to 6.77°, respectively. Additionally, incorporating other modalities alongside IMUs helps improve the performance of the model. 

Selected response items and constructed response (CR) items are often found in the same test. Conventional psychometric models for these two types of items typically focus on using the scores for correctness of the responses. Recent research suggests, however, that more information may be available from the CR items than just scores for correctness. In this study, we describe an approach in which a statistical topic model along with a diagnostic classification model (DCM) was applied to a mixed item format formative test of English and Language Arts. The DCM was used to estimate students’ mastery status of reading skills. These mastery statuses were then included in a topic model as covariates to predict students’ use of each of the latent topics in their written answers to a CR item. This approach enabled investigation of the effects of mastery status of reading skills on writing patterns. Results indicated that one of the skills, Integration of Knowledge and Ideas, helped detect and explain students’ writing patterns with respect to students’ use of individual topics.